Associate Staff Engineer - Data Engineer

- Snowflake Cost Optimization: Monitor and optimize Snowflake compute and storage costs. This includes warehouse sizing and auto-suspend tuning, query profiling, clustering key strategies, materialization choices, and implementing resource monitors to control spend. - Data Pipeline Development: Design and build robust ELT/ETL data pipelines to ingest, transform, and deliver data from diverse sources (ERP, MES, IoT, APIs, flat files) into Snowflake/ AWS Glue/ Lambda. Automate workflows using orchestration tools and Python scripting. - Data Quality & Governance: Implement data quality checks, lineage tracking, and documentation standards. Champion data governance practices to ensure trusted, reliable data across the organization.

- Advanced SQL skills for complex transformations, window functions, CTEs, and analytical queries. - Proficiency in Python for data pipeline development, automation, scripting, and API integrations. - Experience with dashboard/BI tools (Power BI, Tableau) including data source optimization and DAX/LOD calculations.

- Strong dbt proficiency: model development, Jinja/macros, packages, incremental models, snapshots, exposures, and CI/CD integration. - Advanced SQL skills for complex transformations, window functions, CTEs, and analytical queries. - Proficiency in Python for data pipeline development, automation, scripting, and API integrations.

Qualifications Must have skills: Cloud development (Strong), DBT, SQL (Expert), Snowflake Company Description

- Experience with dashboard/BI tools (Power BI, Tableau) including data source optimization and DAX/LOD calculations. - Cloud platform experience (Azure, AWS, or GCP) including storage, compute, networking, and infrastructure-as-code basics. Qualifications

You''ll own the data warehouse layer that powers analytics and reporting across the organization. - Develop & Maintain dbt Projects: Build, test, and document dbt models end-to-end — staging, intermediate, and mart layers. Enforce best practices including version control, CI/CD, data contracts, and comprehensive testing (schema, data, and freshness tests). - Snowflake Cost Optimization: Monitor and optimize Snowflake compute and storage costs. This includes warehouse sizing and auto-suspend tuning, query profiling, clustering key strategies, materialization choices, and implementing resource monitors to control spend.

Expectation from the Candidate: - Experience: 3+ years of experience in data engineering, analytics engineering, or a related role, with hands-on Snowflake and dbt experience in a production environment. Technical Prowess:

- Expert-level Snowflake skills: data modeling, performance tuning, query optimization, Snowpark, stored procedures, streams/tasks, data sharing, and cost management. - Strong dbt proficiency: model development, Jinja/macros, packages, incremental models, snapshots, exposures, and CI/CD integration. - Advanced SQL skills for complex transformations, window functions, CTEs, and analytical queries.

Role and Responsibility: - Design & Build Data Models: Architect and develop scalable, performant data models in Snowflake using dimensional modeling (star/snowflake schemas), OBT, and Data Vault patterns. You''ll own the data warehouse layer that powers analytics and reporting across the organization.

- Develop & Maintain dbt Projects: Build, test, and document dbt models end-to-end — staging, intermediate, and mart layers. Enforce best practices including version control, CI/CD, data contracts, and comprehensive testing (schema, data, and freshness tests). - Snowflake Cost Optimization: Monitor and optimize Snowflake compute and storage costs. This includes warehouse sizing and auto-suspend tuning, query profiling, clustering key strategies, materialization choices, and implementing resource monitors to control spend. - Data Pipeline Development: Design and build robust ELT/ETL data pipelines to ingest, transform, and deliver data from diverse sources (ERP, MES, IoT, APIs, flat files) into Snowflake/ AWS Glue/ Lambda. Automate workflows using orchestration tools and Python scripting.

Technical Prowess: - Expert-level Snowflake skills: data modeling, performance tuning, query optimization, Snowpark, stored procedures, streams/tasks, data sharing, and cost management. - Strong dbt proficiency: model development, Jinja/macros, packages, incremental models, snapshots, exposures, and CI/CD integration.

- Proficiency in Python for data pipeline development, automation, scripting, and API integrations. - Experience with dashboard/BI tools (Power BI, Tableau) including data source optimization and DAX/LOD calculations. - Cloud platform experience (Azure, AWS, or GCP) including storage, compute, networking, and infrastructure-as-code basics.